This article focuses on a problem important to automatic machine learning: the automatic processing of a nonpreprocessed time series. The convolutional neural network (CNN) is one of the most popular ...neural network (NN) algorithms for pattern recognition. Seasonal time series with trends are the most common data sets used in forecasting. Both the convolutional layer and the pooling layer of a CNN can be used to extract important features and patterns that reflect the seasonality, trends, and time lag correlation coefficients in the data. The ability to identify such features and patterns makes CNN a good candidate algorithm for analyzing seasonal time-series data with trends. This article reports our experimental findings using a fully connected NN (FNN), a nonpooling CNN (NPCNN), and a CNN to study both simulated and real time-series data with seasonality and trends. We found that convolutional layers tend to improve the performance, while pooling layers tend to introduce too many negative effects. Therefore, we recommend using an NPCNN when processing seasonal time-series data with trends. Moreover, we suggest using the Adam optimizer and selecting either a rectified linear unit (ReLU) function or a linear activation function. Using an NN to analyze seasonal time series with trends has become popular in the NN community. This article provides an approach for building a network that fits time-series data with seasonality and trends automatically.
Humans are essentially sterile during gestation, but during and after birth, every body surface, including the skin, mouth, and gut, becomes host to an enormous variety of microbes, bacterial, ...archaeal, fungal, and viral. Under normal circumstances, these microbes help us to digest our food and to maintain our immune systems, but dysfunction of the human microbiota has been linked to conditions ranging from inflammatory bowel disease to antibiotic-resistant infections. Modern high-throughput sequencing and bioinformatic tools provide a powerful means of understanding the contribution of the human microbiome to health and its potential as a target for therapeutic interventions. This chapter will first discuss the historical origins of microbiome studies and methods for determining the ecological diversity of a microbial community. Next, it will introduce shotgun sequencing technologies such as metagenomics and metatranscriptomics, the computational challenges and methods associated with these data, and how they enable microbiome analysis. Finally, it will conclude with examples of the functional genomics of the human microbiome and its influences upon health and disease.
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The catalytic oxidative coupling of methane (OCM) to C2 hydrocarbons with oxygen (O2‐OCM) has garnered renewed worldwide interest in the past decade due to the emergence of enormous new shale gas ...resources. However, the C2 selectivity of typical OCM processes is significantly challenged by overoxidation to COx products. Other gaseous reagents such as N2O, CO2, and S2 have been investigated to a far lesser extent as alternative, milder oxidants to replace O2. Although several authoritative review articles have summarized OCM research progress in depth, recent oxidative coupling developments using alternative oxidants (X‐OCM) have not been overviewed in detail. In this perspective, we review and analyze OCM research results reporting the implementation of N2O, CO2, S2, and other non‐O2 oxidants, highlighting the unique chemistries of these systems and their advantages/challenges compared to O2‐OCM. Current outlook and potential areas for future study are also discussed.
The catalytic oxidative coupling of methane to C2 products with O2 (O2‐OCM) is challenged by overoxidation to CO and CO2, despite extensive research. OCM with alternative oxidants such as N2O, CO2, S2 may provide a route to higher C2 selectivities. This Review analyzes progress on catalytic OCM with alternative oxidants, discussing the current status and future prospects.
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Summary
Background
Epidemiology data regarding hidradenitis suppurativa (HS) are conflicting and prevalence estimates vary 80‐fold, from 0·05% in a population‐based study to 4%.
Objectives
To assess ...the hypothesis that previous population‐based studies underestimated true HS prevalence by missing undiagnosed cases.
Methods
We performed a population‐based observational and case–control study using the U.K. Clinical Practice Research Datalink (CPRD) linked to hospital episode statistics data. Physician‐diagnosed cases in the CPRD were identified from specific Read codes. Algorithms identified unrecognized ‘proxy’ cases, with at least five Read code records for boils in flexural skin sites. Validation of proxy cases was undertaken with general practitioner (GP) questionnaires to confirm criteria‐diagnosed cases. A case–control study assessed disease associations.
Results
On 30 June 2013, 23 353 physician‐diagnosed HS cases were documented in 4 364 308 research‐standard records. In total, 68 890 proxy cases were identified, reduced to 10 146 criteria‐diagnosed cases after validation, extrapolated from 107 completed questionnaires (61% return rate). Overall point prevalence was 0·77% 95% confidence interval (CI) 0·76–0·78%. An additional 18 417 cases had a history of one to four flexural skin boils. In physician‐diagnosed cases, odds ratios (ORs) for current smoker and obesity (body mass index > 30 kg m‐2) were 3·61 (95% CI 3·44–3·79) and 3·29 (95% CI 3·14–3·45). HS was associated with type 2 diabetes, Crohn disease, hyperlipidaemia, acne and depression, and not associated with ulcerative colitis or polycystic ovary syndrome.
Conclusions
Contrary to results of previous population‐based studies, HS is relatively common, with a U.K. prevalence of 0·77%, one‐third being unrecognized, criteria‐diagnosed cases using the most stringent disease definition. If individuals with probable cases are included, HS prevalence rises to 1·19%.
What's already known about this topic?
Previous population‐based studies suggest that the prevalence of hidradenitis suppurativa (HS) may be as low as 0·05% but existing studies have not quantified undiagnosed cases.
What does this study add?
Analysis of 4·3 million research‐standard records in the U.K. Clinical Practice Research Datalink demonstrates a HS prevalence of 0·77% using the most stringent disease definition 95% confidence interval (CI) 0·76–0·78%, one‐third being undiagnosed cases, rising to 1·19% (95% CI 1·18–1·20%) if probable cases are included.
Linked Comment: Sbidian. Br J Dermatol 2018; 178:831–832.
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Nucleotide sequencing has become increasingly common and affordable, and is now a vital tool for studies of the human microbiome. Comprehensive microbial community surveys such as MetaHit and the ...Human Microbiome Project have described the composition and molecular functional profile of the healthy (normal) intestinal microbiome. This knowledge will increase our ability to analyze host and microbial DNA (genome) and RNA (transcriptome) sequences. Bioinformatic and statistical tools then can be used to identify dysbioses that might cause disease, and potential treatments. Analyses that identify perturbations in specific molecules can leverage thousands of culture-based isolate genomes to contextualize culture-independent sequences, or may integrate sequence data with whole-community functional assays such as metaproteomic or metabolomic analyses. We review the state of available systems-level models for studies of the intestinal microbiome, along with analytic techniques and tools that can be used to determine its functional capabilities in healthy and unhealthy individuals.
New microbial genomes are constantly being sequenced, and it is crucial to accurately determine their taxonomic identities and evolutionary relationships. Here we report PhyloPhlAn, a new method to ...assign microbial phylogeny and putative taxonomy using >400 proteins optimized from among 3,737 genomes. This method measures the sequence diversity of all clades, classifies genomes from deep-branching candidate divisions through closely related subspecies and improves consistency between phylogenetic and taxonomic groupings. PhyloPhlAn improved taxonomic accuracy for existing and newly sequenced genomes, detecting 157 erroneous labels, correcting 46 and placing or refining 130 new genomes. We provide examples of accurate classifications from subspecies (Sulfolobus spp.) to phyla, and of preliminary rooting of deep-branching candidate divisions, including consistent statistical support for Caldiserica (formerly candidate division OP5). PhyloPhlAn will thus be useful for both phylogenetic assessment and taxonomic quality control of newly sequenced genomes. The final phylogenies, conserved protein sequences and open-source implementation are available online.
Individuals often avoid or delay seeking professional help for mental health problems. Stigma may be a key deterrent to help-seeking but this has not been reviewed systematically. Our systematic ...review addressed the overarching question: What is the impact of mental health-related stigma on help-seeking for mental health problems? Subquestions were: (a) What is the size and direction of any association between stigma and help-seeking? (b) To what extent is stigma identified as a barrier to help-seeking? (c) What processes underlie the relationship between stigma and help-seeking? (d) Are there population groups for which stigma disproportionately deters help-seeking?
Five electronic databases were searched from 1980 to 2011 and references of reviews checked. A meta-synthesis of quantitative and qualitative studies, comprising three parallel narrative syntheses and subgroup analyses, was conducted.
The review identified 144 studies with 90,189 participants meeting inclusion criteria. The median association between stigma and help-seeking was d = - 0.27, with internalized and treatment stigma being most often associated with reduced help-seeking. Stigma was the fourth highest ranked barrier to help-seeking, with disclosure concerns the most commonly reported stigma barrier. A detailed conceptual model was derived that describes the processes contributing to, and counteracting, the deterrent effect of stigma on help-seeking. Ethnic minorities, youth, men and those in military and health professions were disproportionately deterred by stigma.
Stigma has a small- to moderate-sized negative effect on help-seeking. Review findings can be used to help inform the design of interventions to increase help-seeking.
Objective:The author examined patient demographic, clinical, payment, and geographic factors associated with admission to low-safety inpatient psychiatric facilities.Methods:Massachusetts all-payer ...2017 discharge data (N=39,128 psychiatric patients) were linked to facility-level indicators of safety (N=38 facilities). A composite of safety was created by averaging standardized measures of restraint and seclusion as well as 5-year averages of overall, substantiated, and abuse-related (i.e., verbal, physical, or sexual) complaints per 1,000 discharges (α=0.73). This composite informed quintile groups of safety performance. A series of multinomial regression models were fit, with payment and geography added separately.Results:Notable factors independently associated with admission to low-safety facilities were belonging to a racial or ethnic minority group compared with being a White patient (for non-Hispanic Black, relative risk ratio RRR=1.71, p<0.01; for non-Hispanic Asian, RRR=5.60, p<0.01; for non-Hispanic “other” race, RRR=2.17, p<0.01; and for Hispanic-Latinx, RRR=1.29, p<0.01) and not having private insurance (for self-pay or uninsured, RRR=2.40, p<0.01; for Medicaid, RRR=1.80, p<0.01; and for Medicare, RRR=1.31, p<0.01).Conclusions:To the best of the author’s knowledge, this is the first study to examine differences in admission to low-safety inpatient psychiatric facilities. Even after accounting for potential clinical, geographic, and insurance mediators of structural racism, stark racial and ethnic inequities were found in admission to low-safety inpatient psychiatric facilities. In addition to addressing safety performance, policy makers should invest in gaining a better understanding of how differences in community-based referrals, mode of transport (e.g., police or self), and deliberate or unintentional steering and selection affect admissions and outcomes.
Exposure to traffic-related air pollution (TRAP) is associated with accelerated cognitive aging and higher dementia risk in human populations. Rodent brains respond to TRAP with activation of ...astrocytes and microglia, increased inflammatory cytokines, and neurite atrophy. A role for Toll-like receptor 4 (TLR4) was suggested in mouse TLR4-knockouts, which had attenuated lung macrophage responses to air pollution.
To further analyze these mechanisms, we examined mixed glial cultures (astrocytes and microglia) for RNA responses to nanoscale particulate matter (nPM; diameter <0.2 μm), a well-characterized nanoscale particulate matter subfraction of TRAP collected from a local freeway (Morgan et al. Environ Health Perspect 2011; 119,1003-1009, 2011). The nPM was compared with responses to the endotoxin lipopolysaccharide (LPS), a classic TLR4 ligand, using Affymetrix whole genome microarray in rats. Expression patterns were analyzed by significance analysis of microarrays (SAM) for fold change and by weighted gene co-expression network analysis (WGCNA) to identify modules of shared responses between nPM and LPS. Finally, we examined TLR4 activation in hippocampal tissue from mice chronically exposed to nPM.
SAM and WGCNA analyses showed strong activation of TLR4 and NF-κB by both nPM and LPS. TLR4 siRNA attenuated TNFα and other inflammatory responses to nPM in vitro, via the MyD88-dependent pathway. In vivo, mice chronically exposed to nPM showed increased TLR4, MyD88, TNFα, and TNFR2 RNA, and decreased NF-κB and TRAF6 RNA TLR4 and NF-κB responses in the hippocampus.
These results show TLR4 activation is integral in brain inflammatory responses to air pollution, and warrant further study of TLR4 in accelerated cognitive aging by air pollution.
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The Centers for Medicare and Medicaid Services implemented the Inpatient Psychiatric Facility Quality Reporting Program in 2012, which publicly reports facilities’ performance on restraint and ...seclusion (R-S) measures. Using data from Massachusetts, we examined whether nonprofits and for-profits responded differently to the program on targeted indicators, and if the program had a differential spillover effect on nontargeted indicators of quality by ownership. Episodes of R-S (targeted), complaints (nontargeted), and discharges were obtained for 2008-2017 through public records requests to the Commonwealth of Massachusetts. Using difference-in-differences estimators, we found no differential changes in R-S between for-profits and nonprofits. However, for-profits had larger increases in overall complaints, safety-related complaints, abuse-related complaints, and R-S-related complaints compared with nonprofits. This is the first study to examine the effects of a national public reporting program among psychiatric facilities on nontargeted measures. Researchers and policymakers should further scrutinize intended and unintended consequences of performance-reporting programs.
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